{"id":"W2093400716","doi":"10.1007/s10664-015-9379-3","title":"What are mobile developers asking about? A large scale study using stack overflow","year":2015,"lang":"en","type":"article","venue":"Empirical Software Engineering","topic":"Software Engineering Research","field":"Computer Science","cited_by":311,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Mobile device; World Wide Web; Mobile computing; Latent Dirichlet allocation; Context (archaeology); Software; Popularity; Mobile Web; Data science; Mobile technology; Software development; Topic model; Telecommunications; Artificial intelligence; Operating system","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001120452,0.0004744451,0.0005188186,0.0003925893,0.0001758964,0.0009113792,0.001375852,0.0001787237,0.00001810322],"category_scores_gemma":[0.002266109,0.0004836988,0.0001300408,0.001766982,0.00002694621,0.002017454,0.001122093,0.0006774085,0.0001010762],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007542131,"about_ca_system_score_gemma":0.0002690263,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002483247,"about_ca_topic_score_gemma":0.00000977492,"domain_scores_codex":[0.9959553,0.00009348449,0.0004887547,0.0009341817,0.001289963,0.001238339],"domain_scores_gemma":[0.997054,0.0007595181,0.0000878334,0.001064655,0.0003142186,0.0007197637],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001157521,0.0004152484,0.7260981,0.00008403755,0.00009483498,0.0003131398,0.0100103,0.2600571,0.00004521414,0.000007871424,0.001063283,0.001799311],"study_design_scores_gemma":[0.003679944,0.0006789127,0.4629442,0.0008305109,0.00004796964,0.0001682167,0.004623929,0.4958116,0.0007100027,0.00005089685,0.02776353,0.002690286],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5360192,0.0006604578,0.4604915,0.00003418926,0.00121448,0.0003928964,0.000003237804,0.001181495,0.000002550887],"genre_scores_gemma":[0.8961228,0.00001279881,0.1031221,0.0001315801,0.0002757363,0.0001310987,0.000004240126,0.0001100424,0.0000897048],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3601035,"threshold_uncertainty_score":0.9997615,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0514213064798872,"score_gpt":0.324397707768517,"score_spread":0.2729764012886298,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}